Transactions of the Institute of Systems, Control and Information Engineers
Online ISSN : 2185-811X
Print ISSN : 1342-5668
ISSN-L : 1342-5668
Proposal of a Multi-objective Genetic Algorithm for Noisy Fitness Functions
Hirotaka KAJI
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2005 Volume 18 Issue 12 Pages 423-432


In this paper, genetic algorithms for multi-objective optimization problems with uncertainty, which attract attention for applications to simulation-based and experiment-based optimization of real systems, are discussed. First, difficulties faced by conventional multi-objective GAs in their application to multi-objective optimization of noisy fitness functions are described. Second, to cope with these problems, a multi-objective GA that has a fitness estimation method and a new selection operator is proposed. The effectiveness of the proposed method is demonstrated by numerical simulations and real-world experiments.

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